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Record W4213155555 · doi:10.1364/optica.443440

Ultrafast magnetic scattering on ferrimagnets enabled by a bright Yb-based soft x-ray source

2022· article· en· W4213155555 on OpenAlexafffund
G. Fan, Katherine Légaré, Vincent Cardin, Xinhua Xie, Reza Safaei, Edgar Kaksis, G. Andriukaitis, A. Pugžlys, Bruno E. Schmidt, Jean‐Pierre Wolf, M. Hehn, G. Malinowski, Boris Vodungbo, Emmanuelle Jal, J. Lüning, Nicolas Jaouen, Gaia Giovannetti, Francesca Calegari, Zhensheng Tao, Andrius Baltuška, François Légaré, Tadas Balčiūnas

Bibliographic record

VenueOptica · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicLaser-Matter Interactions and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
FundersNational Key Research and Development Program of ChinaHORIZON EUROPE Marie Sklodowska-Curie ActionsInstitut national des sciences de l'UniversNatural Sciences and Engineering Research Council of CanadaCentre National de la Recherche ScientifiqueAgence Nationale de la RechercheAustrian Science FundNational Natural Science Foundation of ChinaFonds de recherche du Québec – Nature et technologiesHorizon 2020 Framework ProgrammeDeutsche Forschungsgemeinschaft
KeywordsPhysics

Abstract

fetched live from OpenAlex

Development of ultrafast table-top x-ray sources that can map various spin, orbital, and electronic configurations and reordering processes on their natural time and length scales is an essential topic for modern condensed matter physics as well as ultrafast science. In this work, we demonstrate spatiotemporally resolved resonant magnetic scattering (XRMS) to probe the inner-shell 4d electrons of a rare-earth (RE) composite ferrimagnetic system using a bright > 200 e V soft x-ray high harmonic generation (HHG) source, which is relevant for future energy-efficient, high-speed spintronic applications. The XRMS is enabled by direct driving of the HHG process with power-scalable, high-energy Yb laser technology. The optimally phase-matched broadband plateau of the HHG offers a record photon flux ( > 2 × 1 0 9 p h o t o n s / s / 1 % bandwidth) with excellent spatial coherence and covers the entire resonant energy range of RE’s N 4 , 5 edges. We verify the underlying physics of our x-ray generation strategy through the analysis of microscopic and macroscopic processes. Using a CoTb alloy as a prototypical ferrimagnetic system, we retrieve the spin dynamics, and resolve a fast demagnetization time of 500 ± 126 f s , concomitant with an expansion of the domain periodicity, corresponding to a domain wall velocity of ∼ 750 m / s . The results confirm that, far from cross-contamination of low-energy absorption edges in multi-element systems, the highly localized states of 4 d electrons associated with the N 4 , 5 edges can provide high-quality core-level magnetic information on par with what can be obtained at the M edges, which is currently accessible only at large-scale x-ray facilities. The analysis also indicates the rich material-, composition-, and probing-energy-dependent driving mechanism of RE-associated multicomponent systems. Considering the rapid emergence of high-power Yb lasers combined with novel nonlinear compression technology, this work indicates potential for next-generation high-performance soft x-ray HHG-based sources in future extremely photon-hungry applications on the table-top scale, such as probing electronic motion in biologically relevant molecules in their physiological environment (liquid phase), and advanced coherent imaging of nano-engineered devices with 5 ∼ 8 n m resolution.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.005
GPT teacher head0.213
Teacher spread0.208 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations24
Published2022
Admission routes2
Has abstractyes

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